Project description:Background Coral reefs belong to the most ecologically and economically important ecosystems on our planet. Yet, they are under steady decline worldwide due to rising sea surface temperatures, disease, and pollution. Understanding the molecular impact of these stressors on different coral species is imperative in order to predict how coral populations will respond to this continued disturbance. The use of molecular tools such as microarrays has provided deep insight into the molecular stress response of corals. Here, we have performed comparative genomic hybridizations (CGH) with different coral species to an Acropora palmata microarray platform containing 13,546 cDNA clones in order to identify potentially rapidly evolving genes and to determine the suitability of existing microarray platforms for use in gene expression studies (via heterologous hybridization). Results Our results showed that the current microarray platform for A. palmata is able to provide biological relevant information for a wide variety of coral species covering both the complex clade as well the robust clade. Analysis of the fraction of highly diverged genes showed a significantly higher amount of genes without annotation corroborating previous findings that point towards a higher rate of divergence for taxonomically restricted genes. Among the genes with annotation, we found many mitochondrial genes to be highly diverged in M. faveolata when compared to A. palmata, while the majority of nuclear encoded genes maintained an average divergence rate. Conclusions The use of present microarray platforms for transcriptional analyses in different coral species will greatly enhance the understanding of the molecular basis of stress and health and highlight evolutionary differences between scleractinian coral species. On a genomic basis, we show that cDNA arrays can be used to identify patterns of divergence. Mitochondrion-encoded genes seem to have diverged faster than nuclear encoded genes in robust corals. Accordingly, this needs to be taken into account when using mitochondrial markers for scleractinian phylogenies.

Project description:Background Coral reefs belong to the most ecologically and economically important ecosystems on our planet. Yet, they are under steady decline worldwide due to rising sea surface temperatures, disease, and pollution. Understanding the molecular impact of these stressors on different coral species is imperative in order to predict how coral populations will respond to this continued disturbance. The use of molecular tools such as microarrays has provided deep insight into the molecular stress response of corals. Here, we have performed comparative genomic hybridizations (CGH) with different coral species to an Acropora palmata microarray platform containing 13,546 cDNA clones in order to identify potentially rapidly evolving genes and to determine the suitability of existing microarray platforms for use in gene expression studies (via heterologous hybridization). Results Our results showed that the current microarray platform for A. palmata is able to provide biological relevant information for a wide variety of coral species covering both the complex clade as well the robust clade. Analysis of the fraction of highly diverged genes showed a significantly higher amount of genes without annotation corroborating previous findings that point towards a higher rate of divergence for taxonomically restricted genes. Among the genes with annotation, we found many mitochondrial genes to be highly diverged in M. faveolata when compared to A. palmata, while the majority of nuclear encoded genes maintained an average divergence rate. Conclusions The use of present microarray platforms for transcriptional analyses in different coral species will greatly enhance the understanding of the molecular basis of stress and health and highlight evolutionary differences between scleractinian coral species. On a genomic basis, we show that cDNA arrays can be used to identify patterns of divergence. Mitochondrion-encoded genes seem to have diverged faster than nuclear encoded genes in robust corals. Accordingly, this needs to be taken into account when using mitochondrial markers for scleractinian phylogenies. Microarray experiments were performed as follows. Appropriate Cy3 and Cy5 labeled DNAs were mixed together in a hybridization buffer containing 0.25% SDS, 25 mM HEPES and 3 × SSC, resulting in a final volume of 70?l. The hybridization mixtures were boiled for 2 min at 99°C and allowed to cool at room temperature for 5 min. The cooled hybridization mixtures were pipetted under an mSeries Lifterslip (Erie Scientific), and hybridization took place in Corning hybridization chambers overnight at 55°C. Microarrays were washed once in 2 × SSC, 0.03% SDS heated to 55 °C for 5 min. followed by one wash in 1 x SSC and another wash in 0.2 x SSC for 5 min each. The slides were kept in 0.2 × SSC until analysis. Slides were dried via centrifugation and scanned using an Axon 4000B scanner. The experimental setup followed a reference design, i.e., all samples were hybridized against the same pool of labeled A. palmata DNA. For each species, a total of four hybridizations were performed, including two dye swap hybridizations in order to account for potential dye bias i.e. two hybridizations with Cy3 labeled M. faveolata DNA against a Cy5 labeled A. palmata reference and two hybridizations with Cy5 labeled M. faveolata DNA against a Cy3 labeled Cy3 A. palmata reference were performed. The same hybridization scheme was used for A. cervicornis and S. radians.

Project description:BackgroundCoral reefs belong to the most ecologically and economically important ecosystems on our planet. Yet, they are under steady decline worldwide due to rising sea surface temperatures, disease, and pollution. Understanding the molecular impact of these stressors on different coral species is imperative in order to predict how coral populations will respond to this continued disturbance. The use of molecular tools such as microarrays has provided deep insight into the molecular stress response of corals. Here, we have performed comparative genomic hybridizations (CGH) with different coral species to an Acropora palmata microarray platform containing 13,546 cDNA clones in order to identify potentially rapidly evolving genes and to determine the suitability of existing microarray platforms for use in gene expression studies (via heterologous hybridization).ResultsOur results showed that the current microarray platform for A. palmata is able to provide biological relevant information for a wide variety of coral species covering both the complex clade as well the robust clade. Analysis of the fraction of highly diverged genes showed a significantly higher amount of genes without annotation corroborating previous findings that point towards a higher rate of divergence for taxonomically restricted genes. Among the genes with annotation, we found many mitochondrial genes to be highly diverged in M. faveolata when compared to A. palmata, while the majority of nuclear encoded genes maintained an average divergence rate.ConclusionsThe use of present microarray platforms for transcriptional analyses in different coral species will greatly enhance the understanding of the molecular basis of stress and health and highlight evolutionary differences between scleractinian coral species. On a genomic basis, we show that cDNA arrays can be used to identify patterns of divergence. Mitochondrion-encoded genes seem to have diverged faster than nuclear encoded genes in robust corals. Accordingly, this needs to be taken into account when using mitochondrial markers for scleractinian phylogenies.

Project description:MotivationAccurate prediction of genes encoding small proteins (on the order of 50 amino acids or less) remains an elusive open problem in bioinformatics. Some of the best methods for gene prediction use either sequence composition analysis or sequence similarity to a known protein coding sequence. These methods often fail for small proteins, however, either due to a lack of experimentally verified small protein coding genes or due to the limited statistical significance of statistics on small sequences. Our approach is based upon the hypothesis that true small proteins will be under selective pressure for encoding the particular amino acid sequence, for ease of translation by the ribosome and for structural stability. This stability can be achieved either independently or as part of a larger protein complex. Given this assumption, it follows that small proteins should display conserved local protein structure properties much like larger proteins. Our method incorporates neural-net predictions for three local structure alphabets within a comparative genomic approach using a genomic alignment of 22 closely related bacteria genomes to generate predictions for whether or not a given open reading frame (ORF) encodes for a small protein.ResultsWe have applied this method to the complete genome for Escherichia coli strain K12 and looked at how well our method performed on a set of 60 experimentally verified small proteins from this organism. Out of a total of 11 407 possible ORFs, we found that 6 of the top 10 and 27 of the top 100 predictions belonged to the set of 60 experimentally verified small proteins. We found 35 of all the true small proteins within the top 200 predictions. We compared our method to Glimmer, using a default Glimmer protocol and a modified small ORF Glimmer protocol with a lower minimum size cutoff. The default Glimmer protocol identified 16 of the true small proteins (all in the top 200 predictions), but failed to predict on 34 due to size cutoffs. The small ORF Glimmer protocol made predictions for all the experimentally verified small proteins but only contained 9 of the 60 true small proteins within the top 200 predictions.Contactjsamayoa@jhu.edu

Project description:BackgroundMicroarray-based Comparative Genomic Hybridization (M-CGH) has been used to characterize the extensive intraspecies genetic diversity found in bacteria at the whole-genome level. Although conventional microarray analytical procedures have proved adequate in handling M-CGH data, data interpretation using these methods is based on a continuous character model in which gene divergence and gene absence form a spectrum of decreasing gene conservation levels. However, whereas gene divergence may yet be accompanied by retention in gene function, gene absence invariably leads to loss of function. This distinction, if ignored, leads to a loss in the information to be gained from M-CGH data. We present here results from experiments in which two genome-sequenced strains of C. jejuni were compared against each other using M-CGH. Because the gene content of both strains was known a priori, we were able to closely examine the effects of sequence divergence and gene absence on M-CGH data in order to define analytical parameters for M-CGH data interpretation. This would facilitate the examination of the relative effects of sequence divergence or gene absence in comparative genomics analyses of multiple strains of any species for which genome sequence data and a DNA microarray are available.ResultsAs a first step towards improving the analysis of M-CGH data, we estimated the degree of experimental error in a series of experiments in which identical samples were compared against each other by M-CGH. This variance estimate was used to validate a Log Ratio-based methodology for identification of outliers in M-CGH data. We compared two genome strains by M-CGH to examine the effect of probe/target identity on the Log Ratios of signal intensities using prior knowledge of gene divergence and gene absence to establish Log Ratio thresholds for the identification of absent and conserved genes.ConclusionThe results from this empirical study validate the Log Ratio thresholds that have been used in other studies to establish gene divergence/absence. Moreover, the analytical framework presented here enhances the information content derived from M-CGH data by shifting the focus from divergent/absent gene detection to accurate detection of conserved and absent genes. This approach closely aligns the technical limitations of M-CGH analysis with practical limitations on the biological interpretation of comparative genomics data.

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Insights into the innate immunome of actiniarians using a comparative genomic approach.

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